route-researcher

name

route-researcher

description

Research mountain routes and generate comprehensive route beta reports for North American peaks, aggregating weather forecasts, avalanche conditions, daylight windows, trip reports, and access info from PeakBagger, SummitPost, WTA, AllTrails, and regional avalanche centers. Use when planning a climb, hike, or scramble, or when asked for route beta, trail conditions, peak research, or mountaineering trip planning.

Route Researcher

Research mountain peaks across North America and generate comprehensive route beta reports combining data from multiple sources including PeakBagger, SummitPost, WTA, AllTrails, weather forecasts, avalanche conditions, and trip reports.

Data Sources: This skill aggregates information from specialized mountaineering websites (PeakBagger, SummitPost, Washington Trails Association, AllTrails, The Mountaineers, and regional avalanche centers). The quality of the generated report depends on the availability of information on these sources. If your target peak lacks coverage on these websites, the report may contain limited details. The skill works best for well-documented peaks in North America.

When to Use This Skill

Use this skill when the user requests:

• Research on a specific mountain peak
• Route beta or climbing information
• Trip planning information for peaks
• Current conditions for mountaineering objectives

Examples:

• "Research Mt Baker"
• "I'm planning to climb Sahale Peak next month, can you research the route?"
• "Generate route beta for Forbidden Peak"

Progress Checklist

Research Progress:

• Phase 1: Peak Identification (peak validated, ID obtained)
• Phase 2: Peak Information Retrieval (coordinates and details obtained)
• Phase 3: Data Gathering (parallel execution)
  • Phase 3a: Python conditions fetch (weather, air quality, daylight, avalanche, peakbagger stats/ascents)
  • Phase 3b: Researcher agents (3 in parallel - web sources + trip reports)
  • Phase 3c: Results aggregated
  • Phase 3d: Access/permits (inline WebSearch)
• Phase 4: Route Analysis (synthesize route, crux, hazards)
• Phase 5: Report Generation (Report Writer agent)
• Phase 6: Report Review & Validation (Report Reviewer agent)
• Phase 7: Completion (user notified, next steps provided)

Orchestration Workflow

Phase 1: Peak Identification

Goal: Identify and validate the specific peak to research.

1. Extract Peak Name from user message

   • Look for peak names, mountain names, or climbing objectives
   • Common patterns: "Mt Baker", "Mount Rainier", "Sahale Peak", etc.

2. Search PeakBagger using peakbagger-cli:

   uvx --with patchright --from "git+https://github.com/dreamiurg/peakbagger-cli.git@v1.10.0" peakbagger peak search "{peak_name}" --format json
   

   • Parse JSON output to extract peak matches
   • Each result includes: peak_id, name, elevation (feet/meters), location, url

3. Handle Multiple Matches:

   • If multiple peaks found: Use AskUserQuestion to present options

     • For each option, show: peak name, elevation, location, AND PeakBagger URL
     • Format each option description as: "[Peak Name] ([Elevation], [Location]) - [PeakBagger URL]"
     • This allows user to click through and verify the correct peak
     • Let user select the correct peak
     • Provide "Other" option if none match

   • If single match found: Confirm with user

     • Present confirmation message with peak details and PeakBagger link
     • Show: "Found: [Peak Name] ([Elevation], [Location])"
     • Include PeakBagger URL in the message so user can verify: "[PeakBagger URL]"
     • Use AskUserQuestion: "Is this the correct peak? You can verify at [PeakBagger URL]"

   • If no matches found:

     • Try peak name variations systematically (see "Peak Name Variations" section):
       • Word order reversal: "Mountain Pratt" → "Pratt Mountain"
       • Title variations: Mt/Mount, St/Saint
       • Add location: Include state or range name
       • Remove titles: Try just the core name
     • Run multiple searches in parallel with different variations
     • Combine results and present best matches to user
     • If still no results, use AskUserQuestion to ask for:
       • A different peak name variation
       • Direct PeakBagger peak ID or URL
       • General PeakBagger search

4. Extract Peak ID:

   • From search results JSON, extract the peak_id field
   • Store for use in subsequent peakbagger-cli commands
   • Also store the PeakBagger URL for reference links

Phase 2: Peak Information Retrieval

Goal: Get detailed peak information and coordinates needed for location-based data gathering.

This phase must complete before Phase 3, as coordinates are required for weather, daylight, and avalanche data.

Retrieve detailed peak information using the peak ID from Phase 1:

uvx --with patchright --from "git+https://github.com/dreamiurg/peakbagger-cli.git@v1.10.0" peakbagger peak show {peak_id} --format json

This returns structured JSON with:

• Peak name and alternate names
• Elevation (feet and meters)
• Prominence (feet and meters)
• Isolation (miles and kilometers)
• Coordinates (latitude, longitude in decimal degrees)
• Location (county, state, country)
• Routes (if available): trailhead, distance, vertical gain
• Peak list memberships and rankings
• Standard route description (if available in routes data)

Error Handling:

• If peakbagger-cli fails: Fall back to WebSearch/WebFetch and note in "Information Gaps"
• If specific fields missing in JSON: Mark as "Not available" in gaps section
• Rate limiting: Built into peakbagger-cli (default 2 second delay)

Once coordinates are obtained from this step, immediately proceed to Phase 3.

Phase 3: Data Gathering

Goal: Gather comprehensive route information from all available sources.

Execution Strategy: Run Python script for deterministic API data + dispatch specialized agents in parallel for web research. This hybrid approach minimizes token usage while maximizing parallelism.

Step 3A: Fetch Conditions Data (Python Script)

Run the conditions fetcher script to gather all API-based data:

cd "{repo_root}/skills/route-researcher/tools"
uv run python fetch_conditions.py \
  --coordinates "{latitude},{longitude}" \
  --elevation {elevation_m} \
  --peak-name "{peak_name}" \
  --peak-id {peak_id} \
  --trailhead "{trailhead_lat},{trailhead_lon}" \
  --distance-mi {round_trip_distance_mi} \
  --gain-ft {total_gain_ft} \
  --start-time "{HH:MM}" \
  --waypoint "{lat1},{lon1}" --waypoint "{lat2},{lon2}"

Optional args: --trailhead enables multi-county path sampling (trailhead→summit); hospital/ranger lookups always run from the summit regardless; --distance-mi/--gain-ft enable time_estimates; --start-time (with distance + gain) enables itinerary; --waypoint (2+) enables bearings.

This returns JSON with:

• weather: 7-day forecast with temperatures, precipitation, freezing levels; each day includes snow_line_note (human-readable framing of freezing level as snow line) and near_summit (bool: true when freezing level within 2000 ft of summit)
• air_quality: AQI ratings and any concerns
• daylight: Full twilight table — astronomical_dawn, nautical_dawn, civil_twilight (dawn), sunrise, sunset, civil_dusk, nautical_dusk, astronomical_dusk; values are null at high latitudes when sun doesn't reach threshold (white nights); daylight_hours, timezone
• time_estimates: Roped/unroped + 3-tier pacing (roped_hr, unroped_hr, fast_hr, moderate_hr, leisurely_hr) — only present when --distance-mi and --gain-ft CLI args are provided
• itinerary: Trip schedule with safety signals (start_time, summit_eta, turnaround_by, return_eta, total_hr, after_dark bool, dusk_cutoff, note) — only present when --start-time, --distance-mi, AND --gain-ft are all provided; after_dark: true is a safety warning that must be prominently surfaced; total_hr is the full round-trip duration in hours
• bearings: Navigation bearings between waypoints (segments[] with bearing_deg, distance_mi, cumulative_distance_mi; total_distance_mi) — only present when 2 or more --waypoint "lat,lon" args are provided
• avalanche: NWAC region and URL for manual check
• peakbagger: Ascent statistics and recent ascents (if peak_id provided)
• counties: Counties traversed trailhead→summit (counties[] with county_name, county_fips, state_name, state_code); sampled bool and sample_points int indicate whether path sampling ran (requires --trailhead); without --trailhead only the summit county is returned
• nearest_hospital: Nearest hospitals/ERs (hospitals[] with name, lat, lon, distance_miles, emergency, and phone/website/address when OSM has them); sorted emergency-first then by distance; max 3
• ranger_station: Nearest ranger stations (stations[] with name, lat, lon, distance_miles, and phone/website/address when present) + optional admin_district (district_name, forest_name, region) when the summit coordinates intersect a USFS ranger district
• campgrounds: Established campgrounds within ~12 mi (20 km) (campgrounds[] with name, lat, lon, distance_miles, camp_type, backcountry, operator, and website when present); backcountry/high camps are NOT included — extract those from trip reports
• gaps: Any API failures noted for report

Run this in parallel with Step 3B — include both the Bash command for fetch_conditions.py and all 3 Task calls in the same response turn to maximize parallelism.

Step 3B: Dispatch Researcher Agents (Parallel)

Dispatch 3 Researcher agents in a single message (all Task calls together). Each agent researches assigned sources and fetches trip report content directly.

Agent 1: PeakBagger + SummitPost

Task(
  subagent_type="general-purpose",
  model="sonnet",
  prompt="""You are a route researcher gathering mountaineering data for {peak_name}.

## Your Assignment
Research from these sources: PeakBagger, SummitPost

**Discover first (web sources):** for SummitPost, run a `site:summitpost.org` WebSearch to get exact URLs, then fetch those (don't WebFetch guessed paths).

## PeakBagger Research
1. Search: "{peak_name} site:peakbagger.com"
2. Extract route descriptions from peak page
3. List recent ascents with trip reports:
   ```bash
   uvx --with patchright --from "git+https://github.com/dreamiurg/peakbagger-cli.git@v1.10.0" peakbagger peak ascents {peak_id} --format json --with-tr --limit 20

4. Identify trip reports with content (word_count > 0)

5. Fetch content for up to 5 recent trip reports using:

   uvx --with patchright --from "git+https://github.com/dreamiurg/peakbagger-cli.git@v1.10.0" peakbagger ascent show {ascent_id} --format json
   

SummitPost Research

1. Search: "{peak_name} site:summitpost.org"

2. Use WebFetch to extract: route name, difficulty, approach, description, hazards

3. If WebFetch fails, use the fetching ladder:

   # Fast path (httpx with browser-like headers, no browser)
   uv run python {repo_root}/skills/route-researcher/tools/cloudscrape.py "{url}"
   
   # If the above returns {"error": ...} or content is blocked/JS-rendered:
   uv run python {repo_root}/skills/route-researcher/tools/cloudscrape.py --render "{url}"
   
   # If --render still returns a Cloudflare challenge page, escalate (needs a display):
   uv run python {repo_root}/skills/route-researcher/tools/cloudscrape.py --render --headed "{url}"
   

Trip Report Extraction

For each report fetched, extract:

• date, author, route conditions, gear mentioned
• Hazards (extract explicitly and separately):
  • Rockfall zones: location on route, conditions, timing guidance mentioned
  • Icefall/serac hazard: location, stability, pre-dawn/timing advice
  • Cornice hazard: location, buildup direction, avoidance notes
• Terrain detail (extract if mentioned):
  • Downclimb sections: location, difficulty, rappel anchors if any
  • River/stream crossings: location, flow conditions, ford difficulty
  • Water sources: named locations, seasonal availability
  • Named camps or bivy sites: name/location, exposure notes

Output Format (return EXACTLY this JSON)

{
  "sources": ["PeakBagger", "SummitPost"],
  "route_info": [
    {"source": "...", "name": "...", "difficulty": "...", "description": "...", "hazards": [...]}
  ],
  "trip_reports": [
    {"source": "...", "date": "...", "author": "...", "url": "...", "summary": "...", "conditions": "...", "has_gpx": false,
     "rockfall": "...", "icefall": "...", "cornices": "...",
     "downclimbs": "...", "crossings": "...", "water_sources": "...", "camps": "..."}
  ],
  "gaps": ["what couldn't be fetched and why"]
}
```"""
)

Agent 2: WTA + Mountaineers + Regional Sources

Task(
  subagent_type="general-purpose",
  model="sonnet",
  prompt="""You are a route researcher gathering mountaineering data for {peak_name}.

## Your Assignment
Research from these sources: WTA, Mountaineers.org, northwesthikers.net, hikeoftheweek.com, Oregon Hikers Field Guide (oregonhikers.org), Cascade Climbers (cascadeclimbers.com), Mountain Project

**Retrieval strategy — discover URLs, then fetch.** For each web source below (except mountaineers.org — use the Mountaineers MCP, see below), FIRST run a `site:` WebSearch (e.g. `"{peak_name} site:wta.org"`, `site:nwhikers.net`, `site:cascadeclimbers.com`) to collect the exact hike-page and individual trip-report URLs. THEN fetch each discovered URL through the fetching ladder. Do not WebFetch a guessed URL — enumerate real URLs first. This recovers reports that one-pass fetching loses to 403/JS blocks.

## WTA Research
1. Search: "{peak_name} site:wta.org"
2. Find the hike page and extract: trail name, difficulty, distance, elevation gain, hazards
3. Get trip reports from AJAX endpoint: {wta_url}/@@related_tripreport_listing
4. Fetch content for up to 5 recent trip reports using the fetching ladder:
   ```bash
   # Fast path first
   uv run python {repo_root}/skills/route-researcher/tools/cloudscrape.py "{trip_report_url}"

   # If output contains {"error": ...} or content is blocked/JS-rendered: